Plasma reactor waste management systems

The University of North Dakota is developing a plasma reactor system for use in closed-loop processing that includes biological, materials, manufacturing, and waste processing. Direct-current, high-frequency, or microwave discharges will be used to produce plasmas for the treatment of materials. The plasma reactors offer several advantages over other systems, including low operating temperatures, low operating pressures, mechanical simplicity, and relatively safe operation. Human fecal material, sunflowers, oats, soybeans, and plastic were oxidized in a batch plasma reactor. Over 98 percent of the organic material was converted to gaseous products. The solids were then analyzed and a large amount of water and acid-soluble materials were detected. These materials could possibly be used as nutrients for biological systems

Bayesian causal inference of cell signal transduction from proteomics experiments

Cell signal transduction describes how a cell senses and processes signals from the environment using networks of interacting proteins. In computational systems biology, investigators apply machine learning methods for causal inference to develop causal Bayesian network models of signal transduction from experimental data. Directed edges in the network represent causal regulatory relationships, and the model can be used to predict the effects of interventions to signal transduction. Causal inference approaches applied to proteomics experiments use statistical associations between observed signaling protein concentrations to infer a causal Bayesian network model, but there is no experimental and analysis framework for applying these methods to this experimental context. The goal of this dissertation is to provide a Bayesian experimental design and modeling framework for causal inference of signal transduction. We evaluate how different high-throughput experimental settings affect the performance of algorithms that detect conditional dependence relationships between proteins. We present a Bayesian active learning approach for designing intervention experiments that reveal the direction of causal influence between proteins. Finally, we present a Bayesian model for inferring the parameters of the conditional probability density functions in a causal Bayesian network. The parameters are directly interpretable as a function of the rate constants in the biochemical reactions between interacting proteins. The work pays special attention to analysis of single-cell snapshot data such as mass cytometry, where each cell is a multivariate cell-level replicate of signal transduction at a single time point. We also address the role of large-scale bulk experiments such as mass-spectrometry-based proteomics, and small-scale time-course experiments in causal inference

The Effect of Hydrogen Partial Pressure on Lignite Liquefaction in a Two-Stage Hot-Charge Batch Autoclave System

The effect of varying hydrogen partial pressure in a two-stage liquefaction process on conversion of North Dakota lignite to THF solubles was studied using the UND hot-charge, time sample, batch autoclave system. Approximately one hundred and fifty grams of moisture- and ash-free (MAF) Zap lignite, three hundred grams of AO4 (Anthracene oil) solvent and seventy five grams of water were reacted in the autoclave unit. Carbon monoxide was used as feed gas for the first stage and varying amounts of hydrogen and carbon monoxide were utilized in the second stage. First stage temperatures ranged from 358 C to 370 C while the second stage temperatures were 429 C to 444 C. Residence times in the first and second stages were 20 and 60 minutes, respectively. Liquid and gas samples were taken at one, three, six, ten, twenty, forty, and sixty minutes during the second stage run period. Overall conversion ranged from 68.7 to 85.0 percent while the distillate yield varied from -7.9 to 25.0 percent based on the MAF coal charge. The soluble residuum yield rose with increasing hydrogen partial pressure from 20.1 to 39.3 percent. Light and middle oil production increased directly with hydrogen partial pressure. When the second stage feed gas consisted of pure carbon monoxide, the heavy oil yield was -15.2 percent. With increasing hydrogen content of the feed gas, the heavy oil yield ranged from -15.2 to 3.2 percent and when 100 percent hydrogen feed gas was used in the second stage, a 3.9 percent yield was produced. Conversion reached a maximum after approximately ten minutes in the second stage. Results indicated that syngas may be a viable feed gas if yields can be increased, perhaps by adding hydrogen sulfide or using a hydrogen donating solvent

Astrophysical Fluids of Novae: High Resolution Pre-decay X-ray spectrum of V4743 Sagittarii

Eight X-ray observations of V4743 Sgr (2002), observed with Chandra and XMM-Newton are presented. The nova turned off some time between days 301.9 and 371, and the X-ray flux subsequently decreased from day 301.9 to 526 following an exponential decline time scale of $(96 \pm 3)$ days. We use the absorption lines present in the SSS spectrum for diagnostic purposes, and characterize the physics and the dynamics of the expanding atmosphere during the explosion of the nova. The information extracted from this first stage is then used as input for computing full photoionization models of the ejecta in V4743 Sgr. The SSS spectrum is modeled with a simple black-body and multiplicative Gaussian lines, which provides us of a general kinematical picture of the system, before it decays to its faint phase (Ness et al. 2003). In the grating spectra taken between days 180.4 and 370, we can resolve the line profiles of absorption lines arising from H-like and He-like C, N, and O, including transitions involving higher principal quantum numbers. Except for a few interstellar lines, all lines are significantly blue-shifted, yielding velocities between 1000 and 6000 km/s which implies an ongoing mass loss. It is shown that significant expansion and mass loss occur during this phase of the explosion, at a rate $\dot{M} \approx (3-5) \times 10^{-4} ~ (\frac{L}{L_{38}}) ~ M_{\odot}/yr$. Our measurements show that the efficiency of the amount of energy used for the motion of the ejecta, defined as the ratio between the kinetic luminosity $L_{\rm kin}$ and the radiated luminosity $L_{\rm rad}$, is of the order of one.Comment: 25 pages, 9 figures. Accepted in book: Recent Advances in Fluid Dynamics with Environmental Applications, pp.365-39

A clinical trial of Varilux Alpha S progressive lenses

The general acceptance of progressive addition multifocal lenses has prompted investigation of their use in the treatment of presbyopic contact lens wearers. Twenty-two candidates were selected fr om the current Pacific University College of Optometry Clinic\u27s records t o compare a new Varilux progressive addition lens to standard near corrections (i.e. · conventional bifocals or half- eyes)

Performative, Informative and Emotive Systems The First Piece of the PIE

This paper distinguishes computer and communications systems that\u27perform\u27 fr om those that\u27inform\u27 and those that deal with emotive aspects of problems. It indicates some of the ways that peformative systems seem to differ from the other kinds, why this distinction is important to both users and designers, and suggests research-some of it currently underway-to investigate this area. Results from this research will allow us to improve existing performative systems and to expand the domain of their application

Three Speech-language Pathology Graduate Programs, One Model: Using Systematic Instruction to Develop Students’ Clinical Decision-making Skills

To prepare graduate students to implement evidence-based practice effectively, educators must integrate instruction on rational clinical decision-making into course curricula. Three faculty members at different universities adopted an educational approach derived from the Rehabilitation Treatment Specification System (RTSS) to teach and assess clinical decision-making in the context of treating acquired cognitive-communication disorders for people with traumatic brain injury. Using treatment theory illustrated in the RTSS, the authors piloted instruction and assessment materials to examine potential usefulness of the approach and effects on student knowledge and confidence in clinical decision-making. The results indicated that the instructional approach effectively bolstered students’ knowledge of and confidence implementing memory-based cognitive-communication intervention. Additionally, using a case-based assessment tool, the authors were able to measure how students modified treatment activities in response to different contextual variables. Implications and suggestions for implementing theory-based instruction in graduate education are discussed